AIMC Topic: Thrombosis

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Machine learning-based prediction model for arteriovenous fistula thrombosis risk: a retrospective cohort study from 2017 to 2024.

BMC nephrology
BACKGROUND: Thrombosis of arteriovenous fistulas represents a prevalent complication among patients undergoing hemodialysis, characterized by a notably high incidence rate. Presently, there is an absence of robust assessment tools capable of predicti...

Design and optimization of an automatic deep learning-based cerebral reperfusion scoring (TICI) using thrombus localization.

Journal of neuroradiology = Journal de neuroradiologie
BACKGROUND: The Thrombolysis in Cerebral Infarction (TICI) scale is widely used to assess angiographic outcomes of mechanical thrombectomy despite significant variability. Our objective was to create and optimize an artificial intelligence (AI)-based...

Machine-learning model for predicting left atrial thrombus in patients with paroxysmal atrial fibrillation.

BMC cardiovascular disorders
OBJECTIVE: Left atrial thrombus (LAT) poses a significant risk for stroke and other thromboembolic complication in patients with atrial fibrillation (AF). This study aimed to evaluate the incidence and predictors of LAT in patients with paroxysmal AF...

Multiscale simulations that incorporate patient-specific neural network models of platelet calcium signaling predict diverse thrombotic outcomes under flow.

PLoS computational biology
During thrombosis, platelets rapidly deposit and activate on the vessel wall, driving conditions such as myocardial infarction and stroke. The complexity of thrombus formation in pathological flow geometries, along with patient-specific pharmacologic...

Enhancing prediction and stratifying risk: machine learning and bayesian-learning models for catheter-related thrombosis in chemotherapy patients.

BMC cancer
BACKGROUND: Catheter-related thrombosis (CRT) is a serious complication in cancer patients undergoing chemotherapy, yet existing risk prediction models demonstrate limited accuracy. This study aimed to evaluate the clinical utility of machine learnin...

Construction and validation of a predictive model for intracardiac thrombus risk in patients with dilated cardiomyopathy: a retrospective study.

BMC cardiovascular disorders
BACKGROUND: Systemic embolic events due to exfoliation of intracardiac thrombus (ICT) are one of the catastrophic complications of dilated cardiomyopathy (DCM). This study intended to develop a prediction model to predict the risk of ICT in patients ...

Sensing the Future of Thrombosis Management: Integrating Vessel-on-a-Chip Models, Advanced Biosensors, and AI-Driven Digital Twins.

ACS sensors
Thrombotic events, such as strokes and deep vein thrombosis, remain a significant global health burden, with traditional diagnostic methods often failing to capture the complex, patient-specific nuances of thrombosis risk. This Perspective explores t...

Rapid Blood Clot Removal via Remote Delamination and Magnetization of Clot Debris.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Micro/nano-scale robotic devices are emerging as a cutting-edge approach for precision intravascular therapies, offering the potential for highly targeted drug delivery. While employing micro/nanorobotics for stroke treatment is a promising strategy ...

Development and validation of machine learning-based prediction model for central venous access device-related thrombosis in children.

Thrombosis research
BACKGROUND: Identifying independent risk factors and implementing high-quality assessment tools for early detection of patients at high risk of central venous access device (CVAD)-related thrombosis (CRT) plays a critical role in delivering timely pr...

Development and validation of an interpretable machine learning model for predicting left atrial thrombus or spontaneous echo contrast in non-valvular atrial fibrillation patients.

PloS one
PURPOSE: Left atrial thrombus or spontaneous echo contrast (LAT/SEC) are widely recognized as significant contributors to cardiogenic embolism in non-valvular atrial fibrillation (NVAF). This study aimed to construct and validate an interpretable pre...